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  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import os\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "matplotlib.use(\"Agg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_path = \"/gpfs/scratch/chgwang/XI/DataBase/Model_1d/evaluation.csv\"\n",
    "df = pd.read_csv(df_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure()\n",
    "tra_loss_list = df.loc[:,\"tra_loss\"]\n",
    "val_loss_list = df.loc[:,\"val_loss\"]\n",
    "plt.plot(range(1,101), tra_loss_list, \"b-\", label=\"training loss\")\n",
    "plt.plot(range(1, 101), val_loss_list, \"r--\", label=\"validation loss\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "fig_path = \"/gpfs/scratch/chgwang/XI/DataBase/Model_figure\"\n",
    "fig_path = os.path.join(fig_path, \"source_training_curve.png\")\n",
    "plt.savefig(fig_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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\n"
     },
     "metadata": {},
     "execution_count": 9
    }
   ],
   "source": [
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}